Abstract: This study aims to identify factors influencing e-scooter injury accidents in Austin due to concerns about rising ridership and insufficient accident data. Using 2018 dockless e-scooter injury data, we employed zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) models. Results indicate the ZIP model better fits the data. Significant… read more
Who loses and who wins in the ride-hailing era? A case study of Austin, Texas
Abstract: This study investigates the impact of ride-hailing on transportation access, particularly in low-density areas. Using data from Austin, Texas, we analyze ride-hailing usage, transit availability, and vehicle ownership across neighborhoods with varying demographics. Our findings reveal that ride-hailing has become an alternative mode of transport for residents in low-income,… read more
Understanding the Relationships Among E-scooter Ridership, Transit Desert Index, and Health-Related Factors
Abstract: This study examines electric scooter (e-scooter) markets in U.S. transit deserts and oases, focusing on Austin, Chicago, Portland, and Minneapolis. Through t-tests, we compared e-scooter ride frequencies in these areas. Results show no significant difference in ride numbers between transit deserts and oases in Austin, Chicago, and Portland. Transit… read more
Look to my Lead: How Does a Leash Affect Perceptions of a Quadruped Robot?
Abstract: In this study, we explore graceful robot navigation in shared spaces, focusing on human-robot dyads resembling a dog and its handler. We examine five conditions: “Fully-Autonomous,” “Remote-Controlled,” “Companion,” “Leading,” and “Guided.” Participants observe these interactions and provide feedback via questionnaires. While initial questionnaire results show few significant differences, comparing… read more
Rental Housing Spot Markets: How Online Information Exchanges Can Supplement Transacted-Rents Data
Abstract: Conventional U.S. rental housing data sources like the American Community Survey and American Housing Survey primarily capture transacted market data, reflecting existing renters’ payments. However, they do not directly reflect spot market conditions—the asking rents for current homeseekers. This study contrasts governmental data with millions of contemporary rental listings,… read more
Longitudinal Social Impacts of HRI over Long-Term Deployments
Abstract: The Longitudinal Social Impacts of HRI over Long-Term Deployments Workshop convenes researchers delving into various facets of understanding extended human-robot interaction deployments. Encompassing longitudinal studies, autonomy in prolonged contexts, and real-world implementations, the workshop aims to advance comprehension of how deployed robot systems influence individuals and societal dynamics. With… read more
What Goes Bump in the Night: Learning Tactile Control for Vision-Occluded Crowd Navigation
Abstract: Expanding the deployment of robots in social environments necessitates safe navigation in contact-prone settings. While collision-free navigation is well-studied, incorporating safe contacts remains underexplored. Traditional approaches mandate robots to freeze upon detecting imminent collisions, risking harm and impeding movement in dense crowds. To address this, we propose a learning-based… read more
Learning Contact-based Navigation in Crowds
ABSTRACT: Navigating crowded environments while intentionally interacting with humans (“contact-based” social navigation) remains largely unexplored, contrasting with extensively studied collision-free social navigation. Traditional approaches demand robots to halt abruptly upon detecting imminent collisions, risking harm or impeding movement in dense crowds. To facilitate meaningful robot integration in bustling social spaces,… read more
Durations of Dockless E-Scooter Trips Before and During the COVID-19 Pandemic in Austin, TX: An Analysis Using Hazard-Based Duration Models
Abstract: The 2019 coronavirus pandemic has profoundly impacted global life, including economies and transportation systems, leading to shifts in travel behaviors. This study investigates the relationship between socio-economic factors and e-scooter trip durations before and during the pandemic. Using hazard-based duration modeling, we analyze data from Austin’s Open Data Portal… read more
Integrating social equity in highway maintenance and rehabilitation programming: A quantitative approach
ABSTRACT: Facing budget constraints and an aging highway infrastructure, decision-makers must balance cost-effectiveness with environmental and social equity considerations. While numerous studies address economic and environmental factors in infrastructure management decisions, few offer quantitative methods for integrating social equity into highway Maintenance and Rehabilitation (M&R) decision-making. This paper proposes four… read more
